Today, software systems that rely on data are ubiquitous, and ensuring the data's quality is an increasingly important challenge as data errors result in annual multi-billion dollar losses. While software debugging and testing have received heavy research attention, less effort has been devoted to data debugging: identifying system errors caused by well-formed but incorrect data. We present continuous data testing (CDT), a low-overhead, delay-free technique that quickly identifies likely data errors. CDT continuously executes domain-specific test queries; when a test fails, CDT unobtrusively warns the user or administrator. We implement CDT in the CON-TEST prototype for the PostgreSQL database management system. A feasibility user study with 96 humans shows that CONTEST was extremely effective in a setting with a data entry application at guarding against data errors: With CONTEST, users corrected 98.4% of their errors, as opposed to 40.2% without, even when we injected 40% false positives into CONTEST's output. Further, when using CONTEST, users corrected data entry errors 3.2 times faster than when using state-of-the-art methods.